std::string ShapeDebugString(TF_Tensor* tensor) {
  // A TF_Tensor cannot have an unknown rank.
  CHECK_GE(TF_NumDims(tensor), 0);
  tensorflow::string s = "[";
  for (int i = 0; i < TF_NumDims(tensor); ++i) {
    if (i > 0) tensorflow::strings::StrAppend(&s, ",");
    int64_t dim = TF_Dim(tensor, i);
    // A TF_Tensor cannot have an unknown dimension.
    CHECK_GE(dim, 0);
    tensorflow::strings::StrAppend(&s, dim);
  }

#include "tensorflow/core/lib/hash/hash.h"

namespace tensorflow {

Operation::Operation(Node* n) : inputs_(GetInputs(n)), node_(n) {}

Output Operation::input(int32_t i) const {
  CHECK_NOTNULL(node_);
  CHECK_GE(i, 0);
  CHECK_LT(i, node_->num_inputs());
  // Handle the case where the input was unknown at the time this
  // Operation was constructed.
  if (inputs_[i].first == nullptr && inputs_[i].second == -1) {

  arguments.reserve(compilation_result->xla_input_shapes.size());

  for (int i = 0; i < compilation_result->xla_input_shapes.size(); ++i) {
    int arg_num = compilation_result->input_mapping[i];
    CHECK_GE(arg_num, missing_ctx_input_prefix);
    const xla::Shape& device_shape = compilation_result->xla_input_shapes[i];
    const xla::Shape& host_shape =
        xla::ShapeUtil::DeviceShapeToHostShape(device_shape);

  tensorflow::Set_TF_Status_from_Status(args->status, status);
}

TF_DataType TF_InputDatatype(TF_OpKernelContext* ctx, int index) {
  auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelContext*>(ctx);
  CHECK_GE(index, 0);                     // Crash OK
  CHECK_LT(index, cc_ctx->num_inputs());  // Crash OK
  return static_cast<TF_DataType>(cc_ctx->input_dtype(index));
}